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1.
Vet Radiol Ultrasound ; 64(4): 775-783, 2023 Jul.
Article in English | MEDLINE | ID: mdl-37322577

ABSTRACT

The aim of this retrospective, secondary analysis study was to quantify the dosimetric impact of the lack of interobserver agreement on gross tumor volume (GTV) delineation for canine meningioma. This study used a previously reported population of 13 dogs with GTVs contoured on CT alone and on registered CT-MR by 18 radiation oncologists. The "true" GTV was generated for each dog using a simultaneous truth and performance-level estimation algorithm, and "true" brain was defined as the whole brain minus true GTV. Treatment plans were generated for each dog and observer combination, using criteria applied to the observer's GTV and brain contours. Plans were then categorized as a pass (met all planning criteria for true GTV and true brain) or fail. A mixed-effects linear regression was performed to examine differences in metrics between CT and CT-MR plans and mixed-effects logistic regression was performed to examine differences in percentages of pass/fail between CT and CT-MRI plans. The mean percent coverage of true GTV by prescribed dose was higher for CT-MR plans than for CT plans (mean difference 5.9%; 95% CI, 3.7-8.0; P < 0.001). There was no difference in the mean volume of true brain receiving ≥24 Gy and in maximum true brain dose between CT plans and CT-MR plans (P ≥ 0.198). CT-MR plans were significantly more likely to pass the criteria for true GTV and true brain than CT plans (OR 1.75; 95% CI, 1.02-3.01; P = 0.044). This study demonstrated significant dosimetric impact when GTV contouring was performed on CT alone compared with CT-MR.


Subject(s)
Dog Diseases , Meningeal Neoplasms , Meningioma , Dogs , Animals , Meningioma/diagnostic imaging , Meningioma/radiotherapy , Meningioma/veterinary , Radiotherapy Planning, Computer-Assisted/veterinary , Radiotherapy Planning, Computer-Assisted/methods , Retrospective Studies , Tomography, X-Ray Computed/veterinary , Tomography, X-Ray Computed/methods , Magnetic Resonance Imaging/veterinary , Magnetic Resonance Imaging/methods , Meningeal Neoplasms/diagnostic imaging , Meningeal Neoplasms/radiotherapy , Meningeal Neoplasms/veterinary , Tumor Burden , Dog Diseases/diagnostic imaging , Dog Diseases/radiotherapy
2.
Cancer Res ; 81(16): 4188-4193, 2021 08 15.
Article in English | MEDLINE | ID: mdl-34185678

ABSTRACT

The National Cancer Institute (NCI) Cancer Research Data Commons (CRDC) aims to establish a national cloud-based data science infrastructure. Imaging Data Commons (IDC) is a new component of CRDC supported by the Cancer Moonshot. The goal of IDC is to enable a broad spectrum of cancer researchers, with and without imaging expertise, to easily access and explore the value of deidentified imaging data and to support integrated analyses with nonimaging data. We achieve this goal by colocating versatile imaging collections with cloud-based computing resources and data exploration, visualization, and analysis tools. The IDC pilot was released in October 2020 and is being continuously populated with radiology and histopathology collections. IDC provides access to curated imaging collections, accompanied by documentation, a user forum, and a growing number of analysis use cases that aim to demonstrate the value of a data commons framework applied to cancer imaging research. SIGNIFICANCE: This study introduces NCI Imaging Data Commons, a new repository of the NCI Cancer Research Data Commons, which will support cancer imaging research on the cloud.


Subject(s)
Diagnostic Imaging/methods , National Cancer Institute (U.S.) , Neoplasms/diagnostic imaging , Neoplasms/genetics , Biomedical Research/trends , Cloud Computing , Computational Biology/methods , Computer Graphics , Computer Security , Data Interpretation, Statistical , Databases, Factual , Diagnostic Imaging/standards , Humans , Image Processing, Computer-Assisted , Pilot Projects , Programming Languages , Radiology/methods , Radiology/standards , Reproducibility of Results , Software , United States , User-Computer Interface
3.
Phys Med ; 49: 77-82, 2018 May.
Article in English | MEDLINE | ID: mdl-29866346

ABSTRACT

INTRODUCTION: Cardiac contraction significantly degrades quality and quantitative accuracy of gated myocardial perfusion SPECT (MPS) images. In this study, we aimed to explore different techniques in motion-compensated temporal processing of MPS images and their impact on image quality and quantitative accuracy. MATERIAL AND METHOD: 50 patients without known heart condition underwent gated MPS. 3D motion compensation methods using Motion Freezing by Cedars Sinai (MF), Log-domain Diffeomorphic Demons (LDD) and Free-Form Deformation (FFD) were applied to warp all image phases to fit the end-diastolic (ED) phase. Afterwards, myocardial wall thickness, myocardial to blood pool contrast, and image contrast-to noise ratio (CNR) were measured in summed images with no motion compensation (NoMC) and compensated images (MF, LDD and FFD). Total Perfusion Defect (TPD) was derived from Cedars-Sinai software, on the basis of sex-specific normal limits. RESULT: Left ventricle (LV) lateral wall thickness was reduced after applying motion compensation (p < 0.05). Myocardial to blood pool contrast and CNR in compensated images were greater than NoMC (p < 0.05). TPD_LDD was in good agreement with the corresponding TPD_MF (p = 0.13). CONCLUSION: All methods have improved image quality and quantitative performance relative to NoMC. LDD and FFD are fully automatic and do not require any manual intervention, while MF is dependent on contour definition. In terms of diagnostic parameters LDD is in good agreement with MF which is a clinically accepted method. Further investigation along with diagnostic reference standards, in order to specify diagnostic value of each technique is recommended.


Subject(s)
Cardiac-Gated Single-Photon Emission Computer-Assisted Tomography , Heart/drug effects , Heart/physiology , Image Processing, Computer-Assisted/methods , Movement , Myocardial Contraction , Myocardial Perfusion Imaging , Adult , Aged , Aged, 80 and over , Female , Humans , Male , Middle Aged , Retrospective Studies , Signal-To-Noise Ratio
4.
Ann Nucl Med ; 31(1): 29-39, 2017 Jan.
Article in English | MEDLINE | ID: mdl-27680021

ABSTRACT

PURPOSE: Prostate imaging is one of the major application of hybrid PET/MRI systems. Inaccurate attenuation maps (µ-maps) derived by direct segmentation (SEG) in which the cortical bone is ignored and the volume of the air in cavities is underestimated is the main challenge of commercial PET/MRI systems for the quantitative analysis of the pelvic region. The present study considered the cortical bone and air cavity along with soft tissue, fat, and background air in the µ-map of the pelvic region using a method based on SEG. The proposed method uses a dedicated imaging technique that increases the contrast between regions and a hybrid segmentation method to classify MR images based on intensity and morphologic characteristics of tissues, such as symmetry and similarity of bony structures. PROCEDURES: Ten healthy volunteers underwent MRI and ultra-low dose CT imaging. The dedicated MR imaging technique uses the short echo time (STE) based on the conventional sequencing implemented on a clinical 1.5T MRI scanner. The generation of a µ-map comprises the following steps: (1) bias field correction; (2) hybrid segmentation (HSEG), including segmenting images into clusters of cortical bone-air, soft tissue, and fat using spatial fuzzy c-means (SFCM), and separation of cortical bone and internal air cavities using morphologic characteristics; (3) the active contour approach for the separation of background air; and (4) the generation of a five-class µ-map for cortical bone, internal air cavity, soft tissue, fat tissue, and background air. Validation was done by comparison with segmented CT images. RESULTS: The Dice and sensitivity metrics of cortical bone structures and internal air cavities were 72 ± 11 and 66 ± 13 and 73 ± 10 and 68 ± 20 %, respectively. High correlation was observed between CT and HSEG-based µ-maps (R 2 > 0.99) and the corresponding sinograms (R 2 > 0.98). CONCLUSIONS: Currently, pelvis µ-maps provided by the current PET/MRI systems and the ultra-short echo time and atlas-based methods tend to be inaccurate. The proposed method acceptably generated a five-class µ-map using only one image.


Subject(s)
Image Processing, Computer-Assisted/methods , Magnetic Resonance Imaging , Multimodal Imaging , Pelvis , Positron-Emission Tomography , Prostate/diagnostic imaging , Healthy Volunteers , Humans , Male
5.
Phys Med ; 32(7): 889-97, 2016 Jul.
Article in English | MEDLINE | ID: mdl-27345258

ABSTRACT

PURPOSE: We developed a high performance portable gamma camera platform dedicated to identification of sentinel lymph nodes (SLNs) and radio-guided surgery for cancer patients. In this work, we present the performance characteristics of SURGEOSIGHT-I, the first version of this platform that can intra-operatively provide high-resolution images of the surveyed areas. METHODS: At the heart of this camera, there is a 43×43 array of pixelated sodium-activated cesium iodide (CsI(Na)) scintillation crystal with 1×1mm(2) pixel size and 5mm thickness coupled to a Hamamatsu H8500 flat-panel multi-anode (64 channels) photomultiplier tube. The probe is equipped with a hexagonal parallel-hole lead collimator with 1.2mm holes. The detector, collimator, and the associated front-end electronics are encapsulated in a common housing referred to as head. RESULTS: Our results show a count rate of ∼41kcps for 20% count loss. The extrinsic energy resolution was measured as 20.6% at 140keV. The spatial resolution and the sensitivity of the system on the collimator surface was measured as 2.2mm and 142cps/MBq, respectively. In addition, the integral and differential uniformity, after uniformity correction, in useful field-of-view (UFOV) were measured 4.5% and 4.6%, respectively. CONCLUSIONS: This system can be used for a number of clinical applications including SLN biopsy and radiopharmaceutical-guided surgery.


Subject(s)
Gamma Cameras , Radionuclide Imaging/instrumentation , Calibration , Equipment Design , Intraoperative Period , Sentinel Lymph Node Biopsy
6.
Mol Imaging Biol ; 17(6): 884-92, 2015 Dec.
Article in English | MEDLINE | ID: mdl-25917750

ABSTRACT

PURPOSE: The aim of this study is to generate a four-class magnetic resonance imaging (MRI)-based attenuation map (µ-map) for attenuation correction of positron emission tomography (PET) data of the head area using a novel combination of short echo time (STE)/Dixon-MRI and a dedicated image segmentation method. PROCEDURES: MR images of the head area were acquired using STE and two-point Dixon sequences. µ-maps were derived from MRI images based on a fuzzy C-means (FCM) clustering method along with morphologic operations. Quantitative assessment was performed to evaluate generated MRI-based µ-maps compared to X-ray computed tomography (CT)-based µ-maps. RESULTS: The voxel-by-voxel comparison of MR-based and CT-based segmentation results yielded an average of more than 95 % for accuracy and specificity in the cortical bone, soft tissue, and air region. MRI-based µ-maps show a high correlation with those derived from CT scans (R (2) > 0.95). CONCLUSIONS: Results indicate that STE/Dixon-MRI data in combination with FCM-based segmentation yields precise MR-based µ-maps for PET attenuation correction in hybrid PET/MRI systems.


Subject(s)
Head/anatomy & histology , Magnetic Resonance Imaging/methods , Positron-Emission Tomography/methods , Head/diagnostic imaging , Humans , Tomography, X-Ray Computed
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